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daunting task of coalescing and using basic data.

But HR departments can overcome those barriers by taking several coordinated steps, including evaluating their current workforce analytics capabilities and unifying all HR analytics strategies, according to an industry analyst.

Not to mention, HR leaders should never lose sight of the need to fully understand analytical data, regardless of the technology they implement, another industry expert recommends. "You need to be able to interpret the data," said Ron Thomas, CEO of the Dubai-based consultancy and research company Great Place to Work. "Anyone can look at data but HR departments need to know what's behind it."

HR needs to implement the right technology

But first things first: HR departments must have the most complete analytics data and that means implementing and using the right technology.

By now, many HR leaders understand the value that analytics can deliver not just to their departments but also to their organizations. HR analytics allow human resources departments to interpret data, recognize issues or trends, and take proactive steps with other departments to boost organizational efficiency and profitability. Basically, analytics allow HR representatives to hire the kind of employee who fits the company mold and has the best chance of meeting organizational goals.

But some HR departments don't realize the potential of analytics because they still use disparate HR systems, according to Helen Poitevin, a Gartner analyst based in France. Because HR departments are using varied data models, they can’t take a nuanced view of even basic HR data, let alone be able to gather every bit of data that’s needed for proper analytics, she said. "You can do analytics with practically no analytics tools, or you can hire a data scientist. But that's difficult to do. It's not scalable and doesn't work across departments," Poitevin said.

Implement tools that specialize in HR analytics

Instead, HR departments should consider implementing tools from vendors that specialize in HR analytics, she said. Using more generic business intelligence (BI) tools requires HR departments to define metrics, and that's often frustrating because definitions first have to be agreed upon and consensus among executives is never easy, she said. Specialized BI data is also difficult to adopt on a broader scale within a company, she said.

The benefit of using specialized HR analytics tools is that metrics are largely predefined, Poitevin said. The metrics for these tools run standard from organization to organization, so the framework of a majority of the data that needs to be brought into the system is already defined. With data extraction techniques established, Poitevin added, there's no need for testing or for HR leaders to have to debate metrics with others in the organization. "They can say, 'This is how it is out of the box,'" she said. "Predefined content is a significant accelerator for HR to embed analytics into its practices."

According to Poitevin, vendors offer organizations one of two choices: standalone technology or embedded programs that mesh with core HR systems. Visier has become one of the strongest players in the standalone platform market, with a strong suit for segmentation analysis, she said. On the other side, Oracle and Workday offer popular embedded analytic programs, she said.

No matter which technology is deployed, the automation of metrics is the key to an HR department getting the most out of its data, Poitevin said. The easier it is to get aligned data out of varied systems, the easier it will be to use data for analytics, she said.

Also, HR and all other departments need to have a shared understanding of the purpose and interpretation of workforce metrics, Poitevin said. An HR analytics team should include individuals with skills in setting information standards to ensure the aligned use of HR data and metrics across an organization, she said.

Thomas couldn’t agree more. A self-described technology agnostic, he recommends that no matter which HR analytics program an organization uses, it must also hire a statistician to make heads or tails of the data.

"You need to build a narrative out of that data. The inability to do so is why a lot of people in the HR space are upset about analytics," he said. "If I was a chief human resources officer, I'd bring in someone who understands the data, who understands the research and who can dig deep and build a narrative that everyone will understand."

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